Systems and methods for providing migration and performance matrices

ABSTRACT

Systems and methods are provided for computing migration and performance matrices. The matrices may provide risk and performance data, as well as different views on the data useful for making and monitoring investment decisions. The migration and performance matrices may bring together data to reflect information on the likelihood that a rated entity will change its current rating within a given time period, information reflecting retention rates, and information describing the effect of changed exchanged rates on different data, for example.

RELATED APPLICATION

This application is a divisional of Application No. 11/191,985, filedJul. 29, 2005 now U.S. Pat. No. 8,200,557, which claims the benefit ofpriority from prior patent application EP 05012313.2, filed Jun. 8,2005, the entire contents of both of which are expressly incorporatedherein by reference.

BACKGROUND

I. Technical Field

The present invention generally relates to computerized systems andmethods for analyzing financial data. More particularly, the inventionrelates to systems and methods for computing and manipulating migrationand performance matrices in order to analyze risk and performance.

II. Background Information

In today's environment of increased competition and converging markets,financial institutions must manage investment risks and returns on anintegrated basis to gain a business advantage. Many financial servicesinstitutions have grown beyond their traditional businesses and havedeveloped diverse operations. Due to increasing complexity, interrelatedrisks, and volatile markets, understanding the value of businesses,individually or collectively, poses a significant challenge to financialinstitutions. In order to meet investor, rating agency, and regulatoryexpectations, financial institutions increasingly require businessprocesses and computing tools that effectively and efficiently assiststrategic and operational decision-making.

Financial institutions are addressing these challenges by developingRisk-Adjusted Performance Measurement (RAPM) and Economic Capitalframeworks. RAPM and economic capital frameworks allow financialinstitutions to aggregate their risk exposures and measure performanceacross diverse products on a consistent basis. Financial institutionsthat use RAPM and economic capital frameworks may move beyondtraditional accounting, regulatory, and rating agency methods ofdetermining capital and performance data for a business.

Building on economic fundamentals and financial risk modeling, theseframeworks allow financial institutions to relate risk withprofitability. In doing so, management may deploy capital moreefficiently, actively manage risks, gain a competitive advantage in themarketplace, and meet regulatory requirements. For example, byconsidering underlying risks (e.g., credit, market, operational, andinsurance) and relationships of risks and products, companies can betterestimate performance based on specific risk and diversification benefitsof a company's operations.

RAPM and economic capital frameworks also provide benefits, such asallowing financial instructions to: analyze economic capital adequacyand usage; view economic/risk relationships in annual budgeting andstrategic planning; allow for the efficient deployment of capital andresources; determine a business, product, and customer mix that yieldsan optimal return; drive an incentive compensation by linkingperformance and risk taken; enhance investor relations, regulatory, andrating agency discussions; and improve their ability to pricetransactions. Aligning decision-making across business processes withina financial institution is a key aspect of RAPM and economic capitalframeworks. As a result, all involved parties, including enterprisemanagement, business units, risk managers, and account managers actwithin a consistent framework. Decisions are based on a commonunderstanding of the key decision criteria, which may cause a singledecision to have a large impact on the overall performance of thefinancial institution. As a result, involved parties have much betterinformation when making decisions.

Performance of a financial institution is measured based on therisk-adjusted performance measurement approach taken. As a result, underand over performance of a company may be easily identified. Toadequately measure performance results, however, one needs to havefurther background on the reasons behind business decisions tounderstand why a specific performance was achieved. The RAPM resultsoften do not provide decision makers with adequate details to makeinformed decisions. Instead, RAPM results deliver static figures that donot provide a sufficient view of business performance. Since decisionmakers prefer to understand the actions and events that drove theperformance of the period under consideration, decision makers requiremore detailed information. Detailed information of the kind needed bydecision makes may be provided by migration matrices.

Typically, migration matrices include detailed information on theactions and events that influenced RAPM results within a specificperiod. In a typical financial institution, credit risk is usually themost important risk type, followed by market risk and then operationalrisk. In particular, a focus of migration matrices is to provide anunderstanding of the credit risk of related businesses. Migrationmatrices deliver in depth information on contributions of the followingactions and events within the period under consideration: changed creditrisk assessment of existing customers; business with new customers;customers lost; business extended with existing customers; businessreduced with existing customers; and changes due to changed currencyexchange rates.

In current implementations of migration matrices, however, the aboveactions and events are measured without relating the available data toRAPM and economic capital frameworks. For example, rating agenciesprovide migration matrices on the likelihood that a business orinvestment, typically referred to by financial institutions as a ratedentity, will change its current rating within a given timeframe.However, business units may separately provide information on retentionrates and controlling units may further provide separately informationon the effect of changed exchange rates for different measures.Accordingly, migration and performance matrices are needed that combinerisk and performance data in one framework that is consistent with theoverall RAPM and economic capital framework.

Furthermore, current software tools are typically not compatible orflexible enough to provide an overview of all of the data pertaining toentities in a financial institution's portfolio. For example, suchsolutions do not take into account measurements such as the inflows andoutflows that occur during a measured time period, currency conversions,or acquisition performance. As a result, decision makers are limited inthe data that is available to them when making key investment decisions.

In view of the foregoing, there is a need for improved systems andmethods for creating migration and performance matrices that relate datafrom RAPM and economic capital frameworks. There is therefore a need fora consistent approach or computerized platform that allows a user toanalyze migration and performance matrices and other data so thatdecision makers are presented with an overview of data that assistsfinancial institution when making and monitoring investment decisions.

SUMMARY

In one embodiment consistent with the present invention, a method isprovided for computing a migration and performance matrix using a dataprocessing system. The method comprises electronically receiving aselection of rated entities from a user; retrieving electronically, froma database, mass data for the selected entities for a rating period; andreading ratings and utilizations for the selected entities for therating period to create a base matrix before aggregation. Further, thebase matrix before aggregation provides a basis for completing themigration and performance matrix.

In another embodiment, a system is provided for computing a migrationand performance matrix. The system comprises a graphical user interfacethat enables a user to make a selection of rated entities; means forreceiving the selection of rated entities from the user; means forretrieving data from a database for the selected entities; and means forreading ratings and utilizations for the selected entities for at leastone rating period to create a base matrix before aggregation. Further,the base matrix before aggregation provides a basis for computing themigration and performance matrix.

In a further embodiment, a method is provided for computing a migrationand performance matrix using a data processing system. The methodcomprises electronically receiving a selection of rated entities from auser; retrieving electronically, from a database, mass data for theselected entities for a rating period; reading ratings and utilizationsfor the selected entities for the rating period to create a base matrixbefore aggregation; aggregating data in the base matrix beforeaggregation to form a base matrix after aggregation; electronicallycomputing at least one additional matrix; using the at least oneadditional matrix to generate a target matrix; and saving the targetmatrix to a database.

In yet another embodiment, a system is provided for computing amigration and performance matrix. The system comprises means forelectronically receiving a selection of rated entities from the user;means for electronically retrieving data from a database for theselected entities; means for reading ratings and utilizations for theselected entities for at least one rating period to create a base matrixbefore aggregation; means for aggregating data in the base matrix beforeaggregation to form a base matrix after aggregation; means forelectronically computing at least one additional matrix; means for usingthe at least one additional matrix to generate a target matrix; andmeans saving the target matrix to a database.

In still yet another embodiment, a database structure is provided forsupporting analysis of financial risk and performance. The databasestructure comprises a list of rated entities that are read from adatabase; data for each of the rated entities for a rating period;ratings and utilizations for the rated entities for the rating period;and an inflow or an outflow status for each rated entity.

In still yet another embodiment, a computer-implemented method isprovided for determining a matrix for use by a financial institution.The method comprises electronically receiving mass data from at leastone database, the mass data including sets of rows and sets of columns,wherein each row corresponds to a record, and each columns includesfields of data characteristics; selecting at least a portion of the massdata and aggregation operations to be carried out by a processor tocreate aggregated records; electronically forming at least one matrixcomprising the aggregated records; and using the at least one matrix tocalculate a target matrix.

In yet another embodiment, a method is provided for performing financialanalysis using a data processing system. The method compriseselectronically receiving a selection of rated entities from a user;electronically retrieving, from a database, mass data for the selectedentities for a rating period; using a processor to read ratings andutilizations for the selected entities for the rating period to create abase matrix before aggregation; aggregating data in the base matrix toform a base matrix after aggregation; electronically computing at leastone additional matrix; using the at least one additional matrix togenerate a target matrix; and providing the target matrix to assist theuser in making a financial decision.

In yet another embodiment, a database structure is provided forsupporting analysis of rated entities by a financial institution. Thedatabase structure comprises a list of rated entities that are read froma database; data for each of the rated entities for a rating period; andratings and utilizations for the rated entities for the rating period.The ratings are assigned to entities that have been added or lost to aportfolio, entities that have reduced or increased business with afinancial institution, and entities that have a low or high credit risk.

It is to be understood that both the foregoing general description andthe following detailed description are exemplary and explanatory onlyand are not restrictive of the invention, as claimed.

BRIEF DESCRIPTION OF THE DRAWINGS

The accompanying drawings, which are incorporated in and constitute apart of this disclosure, illustrate various embodiments and aspects ofthe present invention. In the drawings:

FIG. 1 is a flow diagram of an exemplary method for computing amigration and performance matrix consistent with the present invention;

FIG. 2 illustrates an exemplary user interface for customizing amigration and performance matrix consistent with the present invention;

FIG. 3 is another exemplary interface for customization by a user ofsystems, consistent with the present invention;

FIG. 4 is an exemplary interface for defining granularity fields ofdatabase tables used to calculate the migration and performance matrix;

FIG. 5 is an exemplary interface for setting the data source of therating for the beginning and end of a rating period;

FIG. 6 is an exemplary interface for specifying inflows and outflows;

FIG. 7 is a diagram of an exemplary platform for computing and analyzingmigration and performance matrices;

FIG. 8 is a diagram showing exemplary relationships between matrices,consistent with an embodiment of the present invention;

FIG. 9 is an exemplary table of collected data;

FIG. 10 is an exemplary table including a subset of data shown in FIG.9;

FIG. 11 is an exemplary table prior to aggregation of data;

FIG. 12 is an exemplary table after aggregation of data;

FIG. 13 is an exemplary table of data referred to as portfolio matrix01;

FIG. 14 is an exemplary table of data referred to as portfolio matrix02;

FIG. 15 is an exemplary table of data referred to as in-and-outmigration matrix 03;

FIG. 16 is an exemplary table of data referred to as in-and-out matrixmigration 04;

FIG. 17 is an exemplary table of data referred to as an entities lostmatrix 05;

FIG. 18 is an exemplary table of data referred to as an entities wonmatrix 06;

FIG. 19 is an exemplary table of data referred to as an entityacquisition matrix 07;

FIG. 20 is an exemplary table of data referred to as portfolio aftermigrations at an initial time matrix 10;

FIG. 21 is an exemplary table of data referred to as changed volumematrix 08;

FIG. 22 is an exemplary table of data referred to as acquisitionperformance matrix 09; and

FIG. 23 is an exemplary table showing the resulting migration andperformance matrix, consistent with the present invention.

DETAILED DESCRIPTION

The following detailed description refers to the accompanying drawings.Wherever possible, the same reference numbers are used in the drawingsand the following description to refer to the same or similar parts.While several exemplary embodiments and features of the invention aredescribed herein, modifications, adaptations and other implementationsare possible, without departing from the spirit and scope of theinvention. For example, substitutions, additions or modifications may bemade to the components illustrated in the drawings, and the exemplarymethods described herein may be modified by substituting, reordering, oradding steps to the disclosed methods. Accordingly, the followingdetailed description does not limit the invention. Instead, the properscope of the invention is defined by the appended claims.

Consistent with the present invention, systems and methods are providedfor computing migration and performance matrices. As used herein, a“migration and performance matrix” refers to a data structure includingdata that measures changes and performance statistics of one or morebusinesses. For example, a migration and performance matrix may reflectthe contribution of measured actions and events of a business'performance within a time period under consideration. Actions and eventsthat may be considered for a given time period include, for example,changed credit risk assessment of existing customers; business with newcustomers; customers lost during the time period; business extended withexisting customers; business reduced with existing customers; andchanges due to adjustments in currency exchange rates. Migration andperformance matrices may bring together data from migration matricesreflecting a likelihood that rated entity will change its current ratingwithin a given time period; information reflecting retention rates; andinformation describing the effect of changed exchanged rates ondifferent data, for example. Accordingly, a migration and performancematrix may consolidate data consistent with RAPM and economic capitalframeworks in one data structure. Furthermore, migration and performancematrices consistent with the present invention may be useful to meet therequirements of the New Basel 2 Capital Accord.

In accordance with embodiments of the present invention, migration andperformance matrices can provide a comprehensive view of a portfolio ofdata that is useful, for example, for a bank monitoring investments. Amigration and performance matrix may measure inflows and outflows to aportfolio, as well as acquisitions and acquisition performance. An“acquisition” may include a new company or asset that is acquired by aportfolio and acquisition performance refers to a measurement of thecontribution of an acquired asset to a portfolio over a measured periodof time.

A portfolio comprises a collection of “entities,” which may be rated.Entities are assets such as stocks, bonds, companies, and any otherright or access to present or future economic benefits that arecontrolled by the owner of the entity. The system used to determine therating may be internal to the company, such as a bank, monitoring aportfolio and using its own rating system. Alternately, the ratingsystem may incorporate rating information provided by an externalvendor, such as Moody's Investors Service, which provides credit ratingsto assist investors with analyzing the credit risks associated withfixed-income securities.

Consistent with embodiments of the invention, one or more graphical userinterfaces (GUIs) may be provided for a user to customize data used tocalculate a migration and performance matrix. The GUI may serve as auser-friendly interface to permit a user to measure a portfolio'sperformance. Through the GUI, the user may be prompted with instructionsto configure certain parameters prior to viewing a migration andperformance matrix summarizing the portfolio. These prompts may benon-technical or orientated according to the needs of the user. Further,these prompts may be presented through a set of questions, input forms,tables, diagrams, charts and/or any other form of appropriatepresentation. In one embodiment, one or more screens predefined andstored in memory may provide a user with selectable options to drive theGUI and enter configuration settings by the user. For example, a usermay specify the start and of a time period for which the user would liketo measure a portfolio's performance. The user may also specify whichentities that the user would like to measure.

Consistent with embodiments of the invention, once a user has selectedand configured the data the user would like to analyze, the system mayautomatically generate a migration and performance matrix showing therisk and performance data relevant to the entities selected by the user.

For example, in one embodiment, a list of rated entities may bedisplayed to a user. The list may be retrieved from a databasecontaining rating information for entities. Data may be captured for aselected rating period, which may correspond to start and end datesprovided by the user, for example. Next, ratings and utilization forselected entities are read for the rating period to create a base matrixbefore aggregation. Ratings may reflect an internal or external ratingsystem, such as Moody's. “Utilization” refers to the monetary exposureof a particular entity. In addition, the base matrix before aggregationmay take into consideration an inflow and/or outflow status of anentity. For example, an inflow/outflow status may indicate whether therated entity is new to the portfolio, is a prior entity that was part ofthe portfolio, or is an entity that left the portfolio. Next, data isaggregated to form a base matrix after aggregation. In this step, ratedentities with the same rating migration over the rating period areaggregated. In order to aggregate, a rated entity must have the samerating migration and status, which are discussed more fully below.Matrices reflecting data for the portfolio are then manipulated andanalyzed before being arranged in a target format. The target format mayconstitute a migration and performance matrix, which may be saved to adatabase and/or may be viewed by a user on a display.

Referring to FIG. 1, a flow diagram is provided of an exemplary method100 for computing a migration and performance matrix, consistent with anembodiment of the present invention. At the start of the process, thesystem (see, e.g., FIG. 7) may retrieve a list of rated entities (step110). As part of this step, a user interface (such as a GUI) may beprovided to prompt the user to make selections, such as of a source fileor database containing a list of entities, and/or to specify the startand end of a time period for which the user would like to measure aportfolio's performance. As described above, this may be implementedthrough, for example, a GUI module.

Once the list of rated entities is retrieved, the system may form a basematrix by reading ratings and utilizations for the start and end of therating time period to create a base matrix before aggregation (step120). During this step, large amounts of data for rated entities may beread from one or more historical databases. Mass data may be stored inthe one or more historical databases comprising, for example, millionsof records. Further, the mass data may include sets of rows and sets ofcolumns, where each row corresponds to a record, and each columnincludes fields of data characteristics. A user, such as a employee at abank, will either use an internal rating system or use external ratings.Although the historical database is read, complete records may not beretrieved. Instead, only certain fields of data tables or records thatare needed may be retrieved from the databases. As indicated, a ratedentity carries a rating and the rating method may be an external ratingsystem (such as Moody's, for example) or may be a method devisedinternally by the user.

One of the types of data that may be read for the rating time period foran entity is a utilization value. The term “utilization” refers to ameasurement of a monetary exposure of a rated entity. For example, arated entity may have a line of credit from a bank, or other debts orkey figures. The term “key figure” refers to a monetary exposure thathas been defined by the user. To create the base matrix beforeaggregation, the data may be transformed into a new table where theratings at the beginning and ending of the rating period are listed inone row of the table. One or more intermediary matrices may be formed instep 120 in order to eliminate unnecessary data and/or rearrange datainto an appropriate format. The base matrix before aggregation isdiscussed in more detail with regard to the example of FIG. 10.

As further shown in FIG. 1, in step 130, the mass data is aggregated tocreate a base matrix after aggregation. The base matrix afteraggregation is discussed in more detail with regard to the example ofFIG. 11. Once the base matrix after aggregation is created, the basematrix after aggregation is used to form several additional matricesthat are used in the process, at step 140. Various operations areconducted and efficient parallel processing algorithms may beimplemented to process large volumes of data. In step 140, the basematrix after aggregation is reused repeatedly and additional matricesare created, such as those described more fully below with regard to theexamples of FIGS. 12-21. Next, in step 150, the new matrices arearranged in a target form, which is the migration and performancematrix. In step 160, the migration and performance matrix may be savedto a database, output to a display, and/or transmitted over a network,for example. An exemplary migration and performance matrix is discussedmore fully with regard to FIG. 22.

Referring now to FIG. 2, an exemplary user interface 200 is illustratedthat may be implemented to enable a user to specify parameters togenerate a migration and performance matrix. User interface 200 may bedisplayed when a user selects an option to initiate a calculation from amenu, for example. Further, user interface 200 may allow a user to enterdata through the use of text fields, check boxes, and/or drop downselectable lists, for example.

User interface 200 includes, for example, various fields from which auser may select and specify parameters in order to calculate a migrationand performance matrix to the user's requirements. Assume, for example,that the system is implemented with software, such as bank analyzersoftware. A first grouping of options 210 may allow a user to specifyparameters indicating a source of data used by the bank analyzersoftware. For example, an “ID of Layer” field may allow the user toidentify a database where the software will store the results of thecalculation. A “Matrix ID” field is an identifier that links to usercustomization features that allow a user to customize aspects of thecalculation, as described in connection with FIG. 3. A “Result Matrix”field is an identifier for defining the type of matrix to be calculated.An “Evaluation Currency” field allows the system to perform an internalcurrency conversion if the currency units that are used in the ratedentity data differ or if the user would like to have the matrixcalculated in a different currency. A “Key Date” field is used so thatonly those records are read from the database and used for thecalculation of the matrices that have a validity date less than or equalto the key date. This accounts for versioning of records in the databasesince some databases may store different versions of records reflectingthe state of the data at differing dates. In addition, a “SystemDate/Time” field may be changed by the user, but is typically set to thecurrent date and time.

Through another grouping of options 220, a user may also select theanalysis period. For example, a “Consider Ratings Until” field may beprovided to allow a user to specify how far back to search the databasesto find the last valid rating before beginning the analysis period. A“Start of Period” field establishes when to begin the analysis period.An “End of Period” field indicates the end of the analysis period.Further, in a data collection grouping 230 a “Group ID of Selection”specifies a grouping variable for sorting the selection ID, and a“Selection ID” field defines the database where the rated data isstored.

A user may also make selections through a technical settings grouping240 in user interface 200 to specify technical settings that willinfluence the calculation. For example, a “Parallel Processing” field isa flag indicating whether the process has to be run in parallel modeusing several batch servers for higher performance. A “Test Run” fieldindicates, when its flag is set to a value “X”, that data is not storedto the database but is instead displayed on screen in a report. Also, a“Layout” field may be provided to indicate the layout of the screencolumns, such as which columns to display in which order or sorting.

Referring to FIG. 3, an exemplary user interface 300 is shown forcustomizing a calculation process of bank analyzer software. Forexample, a user may select from a list of options, such as editing amatrix. Software and computer systems consistent with the presentinvention may be highly customizable, and therefore, a user may selectfrom a variety of options, including basic settings, that specify userinterface preferences, for example. In addition, a user may specifyfinancial databases, including historical databases, from which toretrieve rated entity data. General functions, general methods,accounting, and credit risk analyzer options are also available. Asshown in FIG. 3, the options may be displayed using a collapsible listof options, which allows a user to expand the list as needed to changesettings.

FIG. 4 shows another exemplary user interface 400 for defining names ofthe granularity fields of the database tables. For example, a user maychoose a field from a given field repository of the databases where thedescription of the field is already provided. In a similar fashion, asillustrated in FIG. 5, a user interface 500 may be provided for settingthe names of the rating methods that are used to rate the entities inthe database. For example, as shown in FIG. 5, Moody's Rating system maybe specified under the “Name” field for a rating method. Additionally,FIG. 6 shows an exemplary user interface 600 that allows a user tospecify a status of an entity. An entity status may refer to a value of1, 2, or 3, for example. A value of “1” may indicate that an entity is anew rated entity to a group or portfolio. A value of “2” may indicatethat an entity is a prior entity that was already a member of the groupor portfolio. A value of “3” may indicate an entity that left a group.One skilled in the art will recognize that these values are exemplaryand a variety of alternatives may be provided while keeping with thespirit and scope of the present invention.

FIG. 7 is a diagram of an exemplary system platform 700 to implementsystems and methods for computing and analyzing migration andperformance matrices, consistent with the present invention. As shown inFIG. 7, a user interface 710 allows a user to interact with platform700. While only one user interface is shown, there can be multiple userinterfaces, such as GUIs, for allowing a user to interact with platform700. As further shown in FIG. 7, data is stored in a database 720. Forexample, data for rated entities can be stored in database 720 or,alternatively, several database servers and multiple databases may beprovided that are local or connected by a network (not shown) to system700. Other databases may be also be provided, for example, a clusterdatabase 730 may be used to store temporary data and a database 740 maybe used to store matrices and other results of the calculations. Inaddition, the processes discussed above in connection with FIG. 1 may berun in parallel on several batch servers.

For example, a user may operate user interface 710 to initiateprocessing, which, in turn, may access a run control module 750 tocontrol processing. Run control module 750 may, in turn, instruct readrated entities module 760 to access mass data stored in database 720.Read rated entities module 760 may instruct parallel processing module770 to execute processing instructions to format and arrange the massdata into one or more target matrices. In addition, intermediarymatrices may also be created during parallel processing and thesetemporary matrices and any temporary data may be stored in clusterdatabase 730. Parallel processing module 770 may store resultingmatrices in main memory 780, database 740, or may provide results to runcontrol module 750 for display to a user on a display (not shown). Forexample, at the start of the process (see, e.g., FIG. 1), system 700 mayretrieve data used for calculating matrices. Data may be stored in oneor more historical databases, such as, for example, database 720.

Turning to FIG. 8, a diagram 800 is provided that illustrates exemplaryrelationships between matrices, consistent with an embodiment of thepresent invention. For example, as discussed earlier with regard to step120 of FIG. 1, mass data may be retrieved to form a base matrix beforeaggregation by reading ratings data and utilizations over a ratingperiod. An exemplary base matrix before aggregation is discussed in moredetail with regard to FIG. 11. Further, as discussed in connection withstep 130 of FIG. 1, the mass data may be aggregated to create a basematrix after aggregation, an example of which is discussed with regardto FIG. 12.

From the base matrix after aggregation, several additional matrices maybe generated. These additional matrices, which are discussed more fullybelow, include a portfolio matrix 01 (discussed in connection with FIG.13), an in-an-out migration matrix 03 (discussed in connection with FIG.15), an in-and-out migration matrix 04 (discussed in connection withFIG. 16), a portfolio matrix 02 (discussed in connection with FIG. 14),an entities lost matrix 05 (discussed in connection with FIG. 17), andan entities won matrix 06 (discussed in connection with FIG. 18).

Further, additional matrices may be formed or generated by performingoperations upon these matrices. For example, a portfolios at an initialtime matrix 10 (discussed in connection with FIG. 20) may be formed byperforming mathematical operations on portfolio matrix 01,in-and-out-matrix 03, and in-and-out matrix 04. An entity acquisitionmatrix 07 (discussed in connection with FIG. 19) may be formed byperforming mathematical operations on entities lost matrix 05 andentities won matrix 06. A changed volume matrix (discussed in connectionwith FIG. 21) may be formed by performing mathematical operations onportfolio matrix 02, portfolios at an initial time matrix 10, and entityacquisition matrix 07. And, an acquisition performance matrix 09(discussed in connection with FIG. 22) may be formed by performingmathematical operations on entity acquisition matrix 07 and changedvolume matrix 08. One or more of the above matrices may be arranged intoa target matrix, such as a migration and performance matrix (discussedin connection with FIG. 23).

Referring now to FIG. 9, an exemplary table is shown of collected datathat may be retrieved by system 700. The collected data may include oneor more of the following fields. For example, a “Segment ID” (SID) fieldrefers to a business segment, such as automotive, financial, etc. A“Rating Method” (RM) field refers to the type of rating system used forthe entity, such as whether the entity was rated with an internal orexternal rating system. A “Business Partner” (BUPA) field identifies abusiness partner ID of the entity, if any. A “Rating Valid From” (RDAT)field specifies a rating date, which indicates a date from which therating is valid from. A “Rating” (RAT) field may specify a rating of theentity based on the rating method, such as, for example, a rating givenin a letter grade scale or in a numerical scale. The Rating may providean indication of a degree of risk associated with an entity. Inaddition, an “Inflow/Outflow” (IO) field may specify a statusclassification of an entity. For example, an entity status may refer toa value of 1, 2, or 3, for example. A value of “1” may indicate that anentity is a new rated entity to a group or portfolio. A value of “2” mayindicate that an entity is a prior entity that was already a member ofthe group or portfolio. A value of “3” may indicate an entity that lefta group. A “Utilization” (UTIL) field may indicate an appropriateutilization value for an entity, such as a value of an entity is drawingon a credit loan. Further, a “Currency” (CURR) field may specify thecurrency type of a value specified in the utilization field. Forexample, “USD” refers to a currency type of United States dollars.

FIG. 10 is an exemplary matrix that includes a subset of the data shownin FIG. 9. The data included in FIG. 10 includes, for example, theSegment ID, Rating Method, and Business Partner fields. Accordingly,FIG. 10 shows data that is extracted from the table of FIG. 9 to createa new table, as discussed above, for example, in connection with step120 of FIG. 1.

Referring now to FIG. 11, an exemplary table is shown prior to theaggregation of data. As discussed earlier in connection with step 120 ofFIG. 1, mass data is aggregated to form a base matrix beforeaggregation. In the table shown in FIG. 11, the data is provided inanother format where ratings at a start time (t0) and ratings at an endtime (t1) are given in one row of the table. In FIG. 11, the “RT0” fieldindicates a rating of the time series that was most recently assignedbefore t0 was copied to the field RT0. The “RT1” field indicates arating of the time series that was most recently assigned before t1 wascopied to the field RT1. The “UT0” field indicates a utilization of thetime series that was previously assigned to the rating that is now infield RT0. The “UT1” field is a utilization of the time series that waspreviously assigned to the rating that is now in field RT1. The “FX”field is a conversion of the utilizations to the evaluation currencywith the evaluation times t0 and t1. Differences in the utilizations oft0 and t1 that are caused by foreign exchange are stored in the newfield FX. The “CURR” field indicates the type of evaluation currency.

In one embodiment, ratings and utilizations at an initial time (to) andan end time (t1) are read from a historical database to create a basematrix before aggregation. In the next step the mass data is aggregatedand a base matrix after aggregation is obtained. The aggregated basematrix is used to calculate the different matrices used in the remainderof the process. To increase efficiency in processing speed, processingof the data may be done by parallel processing algorithms. For example,a computer-implemented method for automated generic and parallelaggregation of characteristics and key figures of mass data may beintegrated into system platform 700 using parallel processing module770. Examples of computer-implemented methods and systems for automatedgeneric and parallel aggregation of mass data are provided in U.S.Provisional Application No. 60/614,401, entitled “Systems and Methodsfor General Aggregation of Characteristics and Key Figures,” filed Sep.30, 2004, the disclosure of which is incorporated herein by reference inits entirety.

Turning to FIG. 12, an exemplary matrix after aggregation of data isshown. As discussed earlier, this matrix may provide a starting point ora base matrix for several additional matrices and can be re-used severaltimes. For example, the table shown in FIG. 11 is aggregated to resultin the table shown in FIG. 12. The base matrix after aggregationtypically contains significant less data than the originally used massdata. For example, the base matrix after aggregation may contain at mosta few thousand data records.

Consistent with embodiments of the invention, the following providesexemplary options that may be performed to provide different views onthe data. For example, the base matrix after aggregation may beprocessed into one more additional matrices. The one more additionalmatrices, referred to as “result matrices,” may include, for example,portfolio matrices at specified times, migration matrices, acquisitionmatrices, matrices concerning in and out flows, matrices concerningchanges of volume and/or combinations of two or more of these matrices,such as an acquisition and migration matrix.

By way of example, FIG. 13 is an exemplary table of data referred to asportfolio matrix 01. Portfolio matrix 01 may be based on the matrixafter aggregation whether the granularity is reduced to SID, RM, andRT0. For the aggregation to produce portfolio matrix 01, the fields“UT0,” “CNT,” and “FX” are summed together. In addition, the field RT0is set to “not empty” and the inflows are not considered because they donot have a rating at to.

FIG. 14 is an exemplary table of data referred to as portfolio matrix02. Portfolio matrix 02 may be based on the basic matrix afteraggregation. In this matrix, the granularity is reduced to SID, RM, andRT1. In addition, the fields “UT1,” “CNT,” and “FX” are summed togetherand the field RT1 is set to “not empty.” The outflows are not consideredbecause they have no rating at t1.

FIG. 15 shows an exemplary in and out migration matrix 03. Matrix 03 maybe based on the basic matrix after aggregation where the granularity isreduced to SID, RM, RT0 and RT1. Given a specific rating at thebeginning of a period, this matrix shows which rating category acustomer appears in at the end of the period. To form this matrix, thefields “UT0,” “UT1,” “CNT,” and “FX” are summed together. RT0 is set to“not empty” and RT1 is set to “not empty” because the inflows andoutflows are not considered. In addition, RT0 should not equal RT1.

FIG. 16 shows an exemplary in and out migration matrix 04. Given that anentity has a specific rating at the end of a period under consideration,this matrix shows which rating the entity had at the beginning of theperiod. This matrix is generated by transposing matrix 03, and by takingthe inverse of “UT0” and “UT1.”

FIG. 17 shows an exemplary entities lost matrix 05. This matrixindicates which entities (such as customers) have been lost in aspecific time period. The fields “UT0,” “CNT,” and “FX” are summed toarrive at this matrix. In one embodiment, only the records of the basematrix after aggregation are used where the indication of an outflow isgiven. Further, FIG. 18 shows customers an exemplary entities won matrix06. This matrix indicates which entities (again, customers or otherentities) have been won in the specific time period. The fields “UT1,”“CNT,” and “FX” are summed together to arrive at this matrix.

FIG. 19 shows an exemplary entities acquisition matrix 07. The netresults of entities won and entities lost is a key for accessing thesuccess of entities acquisition strategy. To calculate matrix 07, thesum of matrix 05 and matrix 06 is computed. To prepare the calculation,the contents of the fields RT0 and RT1, respectively, and UT0 and UT1,respectively, are at first moved to the fields RING and UTLZ, therebytemporarily modifying matrix 05 and matrix 06. Then the values of UTLZof the modified matrix 05 and matrix 06 are summed based on thegranularity SID, RM, and RTNG. For the result matrix 07, the values RT0,RT1, UT0, and UT1 may be ignored.

FIG. 20 shows an exemplary portfolio after migrations at t1 matrix 10.Taking into account all of the changes of a rating with existingentities allows one to consistently integrate the effect of entityrating migration and to set a consistent basis to later include theeffect of acquiring a new business. Matrix 10 is calculated by summingmatrix 01, matrix 03, and matrix 04. To calculate the sum of thematrices, the ratings “RT0” and “RT1” and the utilizations “UT0” and“UT1” are moved to the fields “RTNG” and “UTLZ.” After that, the valuesof “UTLZ” are summed.

FIG. 21 shows an exemplary changed volume matrix 08. This matrixindicates whether one can extend business with existing customers orother entities. The matrix is calculated as follows: Matrix 08=matrix02−matrix 10−matrix 07. To calculate the difference of the matrices, theratings “RT0” and “RT1” and the utilizations “UT0” and “UT1” are movedto the fields “RTNG” and “UTLZ.” After that, the values of “UTLZ” aresummed.

FIG. 22 shows an exemplary acquisition performance matrix 09. Theoverall acquisition success rate is used to further analyze, forexample, customer retention as well as success of broadening thecustomer base. In may include won customer relations, lost customerrelations, and changed volume with existing customers. The acquisitionperformance matrix 09 is calculated as follows: matrix 09=matrix07+matrix 08. The values of “UTLZ” are summed. The sum means that theutilization (herein referred to as “UTLZ”) is summed for the samecombinations of granularity fields in both matrices. Since matrix 09 hasthe granularity SID, RM, and RTNG, those values of matrix 07 are summedthat have the identical SID, RM, and RTNG.

FIG. 23 shows an example of a resulting migration and performancematrix, consistent with the present invention. By way of example, a userof system platform 700 may make selections from an appropriate interface(such as those discussed in connection with FIG. 2) to compute a targetmatrix, such as, for example, the resulting migration and performancematrix shown in FIG. 23. The migration and performance matrix mayprovide a complete overview of the changes that have occurred to aportfolio within a given time period. To arrive at the matrix shown inFIG. 23, one may arrange previously calculated matrices in an order. Theorder may be given by the field KEY (sorted ascending). In addition, thenew table may be sorted by other fields, such as the fields RING, RT0,and RT1 in ascending order.

Based on the information in the resulting migration and performancematrix, such as that shown in FIG. 23, management and/or other keypersonnel are provided with better information to make financialdecisions; for example, adjust customer acquisition strategy, focus oncustomer retention, and/or react to unfavorable rating migrationeffects. All of these actions may be taken by different parties withinthe financial institution, but the consistent information may facilitateconsistent actions and coordination among managers.

Customer acquisition strategy is of high importance for a financialinstitution, such as a bank, when conducting a growth strategy. Further,at the same time, banks also face a risk of acquiring customers thathave below average rating grades. In the example of FIG. 23, the rowsthat include a key value of 7 allow one to identify the extent of thebank's success in controlling risks while, at the same time, achieving atarget level of growth. The rows that include a key value of 7, in thisexample, show that customers have been acquired having both a goodrating (a letter grade of A) and a low rating (a letter grade of D).

In addition, once a bank has successfully established a relationshipwith a customer, the financial institution may then work to retain thecustomer. The customer will continue to provide business to the bank ifthe bank demonstrates an understanding of the customer and serves thecustomer's needs. Accordingly, as shown in FIG. 23, the rows thatinclude a key value of 8 provide an indication of the bank's success inconducting further business with an existing customer base.

In the example shown in FIG. 23, the bank has lost some business.However, the bank may gain additional important information from FIG. 23in such a situation. In particular, the bank may find it useful to knowhow the rating of entities has changed when a loss in volume of businesswith those entities has occurred. A bank typically reduces or restrictsbusiness with entities that have a low rating and attempts to expandbusiness with entities that have a high rating. In the example, most ofthe volume lost was to entities having a low rating (in this example,letter grades of C and D). Such a loss of volume may be consistent witha business objective to reduce risk. On the other hand, in the example,the bank also faces limited losses with entities that have a higherrating (in this example, letter grades of A and B). These losses may bea warning sign should the bank's strategy include expansion of businessin this customer segment.

Further, the bank may also like to limit the risk in its creditportfolio since it is not possible to completely eliminate credit risk.A high rate of customer default may result in high and unexpected lossesfor the bank. Accordingly, the bank may endeavor to control its exposureto credit risk. As shown in FIG. 23, a comparison of key values of 1 and10 provide the bank with an overview of how the portfolio has changedover time. Unfavorable movements will trigger management decisions toadjust the portfolio in reaction to unfavorable rating migrationeffects.

The foregoing description has been presented for purposes ofillustration. It is not exhaustive and does not limit the invention tothe precise forms or embodiments disclosed. Modifications andadaptations of the invention will be apparent to those skilled in theart from consideration of the specification and practice of thedisclosed embodiments of the invention. For example, the describedimplementations include software, but systems and methods consistentwith the present invention may be implemented as a combination ofhardware and software or in hardware alone. Examples of hardware includecomputing or processing systems, including personal computers, servers,laptops, mainframes, micro-processors and the like. Additionally,although aspects of the invention are described for being stored inmemory, one skilled in the art will appreciate that these aspects canalso be stored on other types of computer-readable media, such assecondary storage devices, for example, hard disks, floppy disks, orCD-ROM, the Internet or other propagation medium, or other forms of RAMor ROM.

Computer programs based on the written description and methods of thisinvention are within the skill of an experienced developer. The variousprograms or program modules can be created using any of the techniquesknown to one skilled in the art or can be designed in connection withexisting software. For example, program sections or program modules canbe designed in or by means of Java, C++, HTML, XML, or HTML withincluded Java applets or in SAP R/3 or ABAP. One or more of suchsoftware sections or modules can be integrated into a computer system orexisting e-mail or browser software.

Moreover, while illustrative embodiments of the invention have beendescribed herein, the scope of the invention includes any and allembodiments having equivalent elements, modifications, omissions,combinations (e.g., of aspects across various embodiments), adaptationsand/or alterations as would be appreciated by those in the art based onthe present disclosure. The limitations in the claims are to beinterpreted broadly based on the language employed in the claims and notlimited to examples described in the present specification or during theprosecution of the application, which examples are to be construed asnon-exclusive. Further, the steps of the disclosed methods may bemodified in any manner, including by reordering steps and/or insertingor deleting steps, without departing from the principles of theinvention. It is intended, therefore, that the specification andexamples be considered as exemplary only, with a true scope and spiritof the invention being indicated by the following claims and their fullscope of equivalents.

What is claimed:
 1. A method for computing a migration and performancematrix using a data processing system, the method comprising: receiving,by a processor, a selection of rated entities from a user; retrieving,by the processor from a database, mass data for the selected ratedentities for a rating period; creating, by the processor, a first basematrix based on ratings and utilizations for the selected rated entitiesfor the rating period; receiving at least one of an inflow or an outflowstatus for the selected rated entities; storing the received status inthe first base rnatrix; forming, by the processor, a second base matrixbased on the first base matrix; forming, by the processor, a pluralityof additional matrices based on the second base matrix; arranging, bythe processor, the additional matrices in an order according to one ormore fields of the additional matrices; and generating, by theprocessor, the migration and performance matrix by combining theadditional matrices in the order.
 2. The method of claim 1, wherein thereceived status indicates whether a rated entity is new to a portfolio,is a prior entity that was part of the portfolio, or is an entity thathas left the portfolio.
 3. The method of claim 1, wherein the arrangingof the additional matrices further comprises arranging the additionalmatrices in one of an ascending order or a descending order according tovalues of the one or more fields of the additional matrices.
 4. Themethod of claim 3, wherein the one or more fields of the additionalmatrices include at least one of a key or a rating associated with therated entities.
 5. The method of claim 1, wherein the additionalmatrices include at least one of a portfolio matrix, a migration matrix,an acquisition matrix, an in-and-out flow matrix, or a change matrix. 6.The method of claim 1, wherein the second base matrix includes a smalleramount of data than the mass data retrieved from the database for theselected rated entities.
 7. A system for computing a migration andperformance matrix, the system comprising: a non-transitorycomputer-readable medium storing instructions; and a processor forperforming a method by executing the instructions, the methodcomprising: receiving a selection of rated entities from the user;retrieving data from a database for the selected rated entities;creating a first base matrix based on ratings and utilizations for theselected rated entities for at least one rating period; receiving atleast one of an inflow or an outflow status for the rated entities;storing the received status in the first base matrix; forming a secondbase matrix based on the first base matrix; forming a plurality ofadditional matrices based on the second base matrix; arranging theadditional matrices in an order according to one or more fields of theadditional matrices; and generating the migration and performance matrixby combining the additional matrices in the order.
 8. The system ofclaim 7, wherein the received status indicates whether a rated entity isnew to a portfolio, is a prior entity that was part of the portfolio, oris an entity that has left the portfolio.
 9. The system of claim 7,wherein the arranging of the additional matrices further comprisesarranging the additional matrices in one of an ascending order or adescending order according to values of the one or more fields of theadditional matrices.
 10. The system of claim 9, wherein the one or morefields of the additional matrices include at least one of a key or arating associated with the rated entities.
 11. The system of claim 7,wherein the additional matrices include at least one of a portfoliomatrix, a migration matrix, an acquisition matrix, an in-and-out flowmatrix, or a change matrix.
 12. The system of claim 7, wherein thesecond base matrix includes a smaller amount of data than the dataretrieved from the database for the selected rated entities.